Evolution of Gene Regulatory Networks under Frequency-Dependent Selection

Gene regulatory networks (GRNs) describe the mutual effects of gene expression among different genes, enabling organisms to adapt to their environment by differentially responding to external inputs. Modelling studies suggest that these networks evolve in response to various selection pressures. However, how GRNs adapt to negative frequency-dependent selection (NFDS), where rare phenotypes are favoured, remains unclear. Using computational and mathematical models, we contrast the evolution of GRNs under different types of selection, eg. stabilising selection and NFDS. Results suggest that while gene expression directly affects phenotypic fitness and is therefore subject to natural selection, network topology undergoes indirect selection due to its influence on properties such as evolvability and robustness. Ultimately, this work seeks to elucidate how the architecture of GRNs responds to distinct selection pressures and its broader implications for evolutionary ecology.